Multivariate linear discrimination of seizures

Kristin K. Jerger, Steven L. Weinstein, Tim Sauer, Steven J. Schiff

Research output: Contribution to journalArticlepeer-review

41 Scopus citations


Objective: To discriminate seizures from interictal dynamics based on multivariate synchrony measures, and to identify dynamics of a pre-seizure state. Methods: A linear discriminator was constructed from two different measures of synchronization: cross-correlation and phase synchronization. We applied this discriminator to a sequence of seizures recorded from the intracranial EEG of a patient monitored over 6 days. Results: Surprisingly, we found that this bivariate measure of synchronization was not a reliable seizure discriminator for 7 of 9 seizures. Furthermore, the method did not appear to reliably detect a pre-seizure state. An association between anti-convulsant dosage, frequency of clinical seizures, and discriminator performance was noted. Conclusions: Using a bivariate measure of synchronization failed to reliably differentiate seizures from non-seizure periods in these data, nor did such methods show reliable detection of a synchronous pre-seizure state. The non-stationary variables of decreasing antiepileptic medication (without available serum concentration measurements), and concomitant increasing seizure frequency contributed to the difficulties in validating a seizure prediction tool on such data. Significance: The finding that these seizures were not a simple reflection of increasing synchronization in the EEG has important implications. The non-stationary characteristics of human post-implantation intracranial EEG is an inherent limitation of pre-resection data sets.

Original languageEnglish (US)
Pages (from-to)545-551
Number of pages7
JournalClinical Neurophysiology
Issue number3
StatePublished - Mar 2005

All Science Journal Classification (ASJC) codes

  • Sensory Systems
  • Neurology
  • Clinical Neurology
  • Physiology (medical)


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